NASA POWER satellite meteorological system is a good tool for obtaining estimates of the temperature-humidity index under Brazilian conditions compared to INMET weather stations data

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Abstract

Heat stress negatively affects livestock, with undesirable effects on animals’ production and reproduction. Temperature and humidity index (THI) is a climatic variable used worldwide to study the effect of heat stress on farm animals. Temperature and humidity data can be obtained in Brazil through the National Institute of Meteorology (INMET), but complete data may not be available due to temporary failures on weather stations. An alternative to obtaining meteorological data is the National Aeronautics and Space Administration Prediction of Worldwide Energy Resources (NASA POWER) satellite-based weather system. We aimed to compare THI estimates obtained from INMET weather stations and NASA POWER meteorological information sources using Pearson correlation and linear regression. After quality check, data from 489 INMET weather stations were used. The hourly, average daily and maximum daily THI were evaluated. We found greater correlations and better regression evaluation metrics when average daily THI values were considered, followed by maximum daily THI, and hourly THI. NASA POWER satellite-based weather system is a suitable tool for obtaining the average and maximum THI values using information collected from Brazil, showing high correlations with THI estimates from INMET and good regression evaluation metrics, and can assist studies that aim to analyze the impact of heat stress on livestock production in Brazil, providing additional data to complement the existing information available in the INMET database.

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Carrara, E. R., Lopes, P. S., Reis, A. C. Z., Silva, J. X., Dias, L. C. de C. M., Schultz, É. B., … Peixoto, M. G. C. D. (2023). NASA POWER satellite meteorological system is a good tool for obtaining estimates of the temperature-humidity index under Brazilian conditions compared to INMET weather stations data. International Journal of Biometeorology, 67(7), 1273–1277. https://doi.org/10.1007/s00484-023-02493-5

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